Ad Advance ced Deep Learn rning for r Comput uter r Vision Prof. Leal-Taixé and Prof. Niessner 1
The Te The Team Lecturers Prof. Dr. Laura Prof. Dr. Matthias Leal-Taixé Niessner Tutors Dave Ji Tim Maxim Chen Hou Meinhardt Maximov Prof. Leal-Taixé and Prof. Niessner 2
Wh What at is this cou ourse e ab abou out • Presentation of advanced Deep Learning methods for various Computer Vision tasks • Focus on new methods, some of them presented only this year! There will be extra references, many opportunities for you to dig deeper into the topics • Research-oriented course Prof. Leal-Taixé and Prof. Niessner 3
Wh While e we e go o ov over er new ew met ethods ods… • You have to come up with your own ideas to solve a specific vision problem! • Strong focus on the practical side: semester-long project where you can put all the knowledge to practice Prof. Leal-Taixé and Prof. Niessner 4
IM IMPORTANT • The project is VERY time-consuming, we are aware. • Since the project is done in teams of 2, we want to avoid students dropping mid-semester! • Please think carefully whether you have the time this semester to dedicate a lot of time to ADL4CV, if not, we kindly ask you to consider to take the course another semester. Prof. Leal-Taixé and Prof. Niessner 5
Course Course orga organizati tion on Prof. Leal-Taixé and Prof. Niessner 6
Ab About t the the lectu ture Theory: 12 lectures • Every Monday 10 10:0 :00-11: 11:30 30h h & Friday 14 14:00-16 16:00h • Seminar Room, 02.13.010 online! • Practical: • • Project to be done in groups of 2 (non-negotiable!) • Presentations during the semester (we will see how) • Final poster presentation https://dvl.in.tum.de/teaching/adl4cv-ss20/ Prof. Leal-Taixé and Prof. Niessner 7
Gra Grading syst g system Exam: tbd tbd • Review: 2 review sessions • Practical part = 2/3 of the grade • Exam = 1/3 of the grade • https://dvl.in.tum.de/teaching/adl4cv-ss20/ Prof. Leal-Taixé and Prof. Niessner 8
Project Pr ct deadli line 24.04., Friday: project presentation • 04.05.: project assignments (projects <-> TAs) • 11.05., 11. , midni night ht: deliver a a 1 1 pag age ab abstrac act of your idea a • for the he project. Until 15.05.: Evaluation of the project and feedback • Prof. Leal-Taixé and Prof. Niessner 9
Project Pr ct evalu luation Presentations: everyone needs to attend! • First present ntat ation: n: first results, , chal halleng nges • – 08 08.06 06: : Groups #1 – 12 12.06: : Groups #2 Prof. Leal-Taixé and Prof. Niessner 10
Project Pr ct evalu luation Presentations: everyone needs to attend! • Second nd present ntat ation: n: al almost final nal results, , ne new w thi hing ngs • yo you tried – 06. 6.07.: : Groups #1 – 10 10.07: : Groups #2 Prof. Leal-Taixé and Prof. Niessner 11
Project Pr ct evalu luation Presentations: everyone needs to attend! • 20.07. 7.: final nal dead adline ne on n report (dead adline ne no noon) n) • Max 4 pages using CVPR template – Final nal present ntat ation n = POS POSTER ER • Date 24.07. 14:00-16:00 – Prof. Leal-Taixé and Prof. Niessner 12
Gra Grading syst g system Exam = 1/3 of the grade • Practical part = 2/3 of the grade • Presentations (2 oral pres. + 1 poster) = 1/3 – Final report = 1/3 – Code/submission = 1/3 – Prof. Leal-Taixé and Prof. Niessner 13
Fo Followin ing u up w wit ith t the p projects Each project will be assigned to a TA and you will • have weekly office hours to discuss the progress These will be announced after the projects are • approved Prof. Leal-Taixé and Prof. Niessner 14
Sli Slides • Moodle is set up! Lecture will be entirely online. • Slides will be posted on Moodle and on the website: https://dvl.in.tum.de/teaching/adl4cv-ss20/ • Questions regarding organization of the course: adl4cv@dvl.in.tum.de • Emails to our individual addresses will not be answered! Prof. Leal-Taixé and Prof. Niessner 15
Te Teams • Teams of two per project! • Moodle is set up! • If you do not have a team – Chat after the lecture – Post it on Moodle Prof. Leal-Taixé and Prof. Niessner 16
Pr Project ct Timeli line • April 24 th Project proposal presentations • May 4 th Projects Assignments (and TA assignments) • May 11 th Abstract Submissions (midnight) • Until May 15 th -> Feedback Projects • 8th + 12 th June -> First presentations (group #1, #2) • 6th + 10 th July -> Second presentation (group #1, #2) • July 20 th -> Deadline report (noon) • July 24 th -> Poster Presentation (14-16h) 51
Ad Advance ced Deep Learn rning for r Comput uter r Vision Prof. Leal-Taixé and Prof. Niessner 52
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